The case studies in this book were written by students at Olin
College, and edited by Lisa Downey and Allen Downey. They
were reviewed by a program committee of faculty at Olin College
who chose the ones that met the criteria of interest and quality.
I am grateful to the program committee and the students.

I invite readers to submit additional case studies. Reports
that meet the criteria will be published in an online supplement
to this book, and the best of them will be included in future
print editions.

The criteria are:

The case study should be relevant to complexity. For an
overview of possible topics, see
http://en.wikipedia.org/wiki/Complexity and
http://en.wikipedia.org/wiki/Complex_systems. Topics
not already covered in the book are particularly welcome.

A good case study might present a seminal paper, reimplement
an important experiment, discuss the results, and explain their
context. Original research is not necessary, and might not
be appropriate for this format, but you could extend existing
results.

A good case study should invite the reader to participate
by including exercises, references to further reading, and
topics for discussion.

The case study should present enough technical detail that
reader could implement the model in a language like Python.

If you use an algorithm or data structure that deserves comment,
you should discuss it. Topics not covered in the book, including
tree algorithms and dynamic programming, are particularly welcome.

If you use a feature of Python or a module that you think
will interest readers, you should discuss it. But you should
stick to modules that are in widespread use and either included
in Python distributions or easy to install.